- The report constructs 10 style factors based on the BARRA model, including valuation factor, growth factor, profitability factor, size factor, Beta factor, momentum factor, liquidity factor, volatility factor, non-linear size factor, and leverage factor[16][17][19] - The construction process for style factors involves detailed formulas, such as the valuation factor (BP = Book to Price = Shareholder equity/Market capitalization), growth factor (SGRO = Sales growth rate derived from regression of past five fiscal years' revenue), profitability factor (ETOP = Earnings-to-price ratio = Net profit TTM/Market capitalization), and others[16][17] - The style factors are tested using weekly rebalancing on the CSI All Share Index (000985.SH) with no transaction fees considered[16][17] - Beta factor, momentum factor, and volatility factor showed strong performance recently, with weekly long-short returns of 4.54%, 4.34%, and 3.81%, respectively[19] - The report tracks 53 stock selection factors across valuation, growth, quality, size, reversal, momentum, liquidity, volatility, dividend, corporate governance, and technical categories[21][22] - Examples of stock selection factors include BP (Book to Price = Shareholder equity/Market capitalization), single-quarter EP (Net profit/Market capitalization), and 240-day momentum (cumulative return excluding the last 20 days)[22] - The construction of single-factor portfolios uses a neutral constraint method to maximize factor exposure while maintaining neutrality in industry and style exposures[62][64][65] - Single-quarter ROE, single-quarter ROA, and single-quarter net profit margin factors performed well across multiple stock pools, such as CSI 300, CSI 500, CSI 800, and CSI 1000[24][28][33][38] - The report evaluates index-enhanced portfolios for CSI 300, CSI 500, CSI 800, CSI 1000, and CSI 300 ESG stock pools using composite factors constructed via rolling 1-year Rank ICIR weighting[56][59][61] - CSI 300 enhanced portfolio achieved weekly excess returns of 0.33%, monthly excess returns of 1.05%, and annual excess returns of 13.02%[59][60] - CSI 1000 enhanced portfolio showed the highest annual excess returns of 15.68% among all portfolios[60] - The ESG-enhanced portfolio under CSI 300 stock pool achieved weekly excess returns of 0.59%, monthly excess returns of 1.09%, and annual excess returns of 7.35%[60] - The optimization model for portfolio construction maximizes exposure to target factors while maintaining neutrality in industry and style exposures, with constraints on stock weights, short selling, and full investment[62][64][65] - The model uses the following formula: $Max$$w^{\prime}$$X_{target}$ $s.t.$$(w-w_{b})^{\prime}X_{ind}=0$ $(w-w_{b})^{\prime}$$X_{Beta}=0$ $|w-w_{b}|\leq1\%$ $w\geq0$ $w^{\prime}B=1$ $w^{\prime}1=1$[62][63][64]

Group 1 - The core viewpoint of the report indicates that valuation factors performed well last week, with the year-to-date excess return of the CSI 2000 index enhancement strategy reaching 23.32% [1] - The report tracks the performance of public index enhancement funds for major broad-based indices, including the CSI 300, CSI 500, CSI 1000, and CSI 2000, providing weekly updates for investor reference [8][9] - The report highlights the top-performing public index enhancement funds for the year, with specific excess returns noted for each fund across different indices [10][16][21][26] Group 2 - The report details the performance of public enhancement funds for the CSI 300 index, noting that the top five funds have year-to-date returns ranging from 24.89% to 32.31%, with corresponding excess returns [10][12] - For the CSI 500 index, the top five funds achieved year-to-date returns between 36.56% and 41.67%, with excess returns noted for each fund [16][19] - The CSI 1000 index enhancement funds also showed strong performance, with the top five funds reporting year-to-date returns from 42.53% to 44.54% [21][24] - The CSI 2000 index enhancement funds had year-to-date returns ranging from 38% to 46.5%, with significant excess returns for the leading funds [26][31] Group 3 - The report analyzes the performance of various factors used in quantitative stock selection models, emphasizing the importance of valuation, profitability, growth, corporate governance, and volume factors [33] - It discusses the methodology for neutralizing factors, particularly the treatment of market capitalization and industry effects, to better reflect the investment logic and stock selection effectiveness [33][34] - The report provides insights into the performance of single factors, highlighting the best and worst performing factors across different stock pools for the past week and year [35][36]

Core Viewpoint - The A-share market in the first three quarters of 2025 has shown a clear divergence in performance, with technology leading while traditional sectors like liquor and real estate lagged behind. The CSI 300 index rose nearly 20%, while the CSI 2000 index saw an increase of over 30%. In this context, index-enhanced funds have emerged as a viable investment strategy, providing a way to earn more without excessive trading [4]. Summary by Index CSI 300 Index - Among 158 CSI 300 index-enhanced funds, the average return for the first three quarters was 19.17%, with an average excess return of 1.77%. 104 funds achieved positive excess returns, representing 65.82% of the total [5]. - The top three funds in terms of excess return were managed by E Fund, China Europe Fund, and Fortune Fund, with E Fund's product achieving an excess return of 17.08% and a total return of 34.11% [6][7]. CSI 500 Index - There are 156 CSI 500 index-enhanced funds, with an average return of 29.60% and an average excess return of 1.48%. The top three funds were managed by Penghua Fund, China Europe Fund, and Huatai-PB Fund, with Penghua's product achieving an excess return of 13.72% and a total return of 41.63% [8][9]. CSI 1000 Index - The CSI 1000 index-enhanced funds totaled 88, with an average return of 34.28% and an average excess return of 8.32%. The top three funds were managed by ICBC Credit Suisse Fund, Changxin Fund, and Penghua Fund, with ICBC's product achieving an excess return of 18.52% and a total return of 44.29% [11][12][13]. CSI 2000 Index - There are 31 CSI 2000 index-enhanced funds, with an average return of 40.74% and an average excess return of 11.11%. The top three funds were managed by Tianhong Fund, Huatai-PB Fund, and Huitianfu Fund, with Tianhong's product achieving an excess return of 18.21% and a total return of 46.48% [14][15].

Core Viewpoint - The quantitative private equity industry has rapidly developed in recent years, outperforming public quantitative funds in terms of performance, with private equity quantitative index enhancement products showing an average return of 31.11% compared to 22.03% for public funds [2][3]. Summary by Category Performance Comparison - As of August 15, 2025, the average return for 398 private equity index enhancement products is 31.11%, with an excess return of 11.50%. In contrast, 382 public equity index enhancement products have an average return of 22.03% and an excess return of 6.04% [2][3]. - The performance of private equity products across different indices shows significant advantages, particularly in the 中证500 and 中证1000 categories, where private equity products have average returns of 29.40% and 35.25%, respectively [9][12]. Leading Products - In the 沪深300 index enhancement category, the top private equity product is "澎湃权益1号" managed by 刘治平, achieving an excess return of ***% [5][7]. - For the 中证500 index enhancement, "兆信中证500指数增强1号A类份额" managed by 唐越 and 胡晨航 leads with an excess return of ***% [10][11]. - The top product in the 中证1000 index enhancement is "今通量化价值成长六号" managed by 钱伟强, with an excess return of ***% [13][15]. - In the 国证/中证2000 index enhancement, "平方和鼎盛中证2000指数增强21号A期" managed by 吕杰勇 and 方壮 ranks first with an excess return of ***% [17][19]. Market Environment - The strong performance of quantitative strategies is attributed to the structural characteristics of the A-share market in the first half of 2025, where small and mid-cap stocks have continued to outperform, and individual stock volatility has increased, creating an ideal trading environment for quantitative strategies [3].

Quantitative Models and Construction Methods - **Model Name**: Maximized Factor Exposure (MFE) Portfolio **Model Construction Idea**: The MFE portfolio aims to maximize the exposure of a single factor while controlling for constraints such as industry exposure, style exposure, stock weight deviation, and turnover rate. This approach evaluates the effectiveness of factors under realistic constraints in enhanced index portfolios [56][57][59] **Model Construction Process**: The optimization model is formulated as follows: $ \begin{array}{ll} max & f^{T}w \\ s.t. & s_{l}\leq X(w-w_{b})\leq s_{h} \\ & h_{l}\leq H(w-w_{b})\leq h_{h} \\ & w_{l}\leq w-w_{b}\leq w_{h} \\ & b_{l}\leq B_{b}w\leq b_{h} \\ & 0\leq w\leq l \\ & 1^{T}w=1 \\ & \Sigma|w-w_{0}|\leq to_{h} \end{array} $ - **Objective Function**: Maximize single-factor exposure, where \( f \) represents factor values, and \( w \) is the stock weight vector - **Constraints**: 1. Style exposure deviation (\( X \)): \( s_{l} \) and \( s_{h} \) are the lower and upper bounds for style factor deviation 2. Industry exposure deviation (\( H \)): \( h_{l} \) and \( h_{h} \) are the lower and upper bounds for industry deviation 3. Stock weight deviation (\( w_{l} \) and \( w_{h} \)): Limits on individual stock weight deviation relative to the benchmark 4. Component weight limits (\( b_{l} \) and \( b_{h} \)): Constraints on the weight of benchmark components 5. No short selling and upper limits on stock weights 6. Full investment constraint: \( 1^{T}w=1 \) 7. Turnover constraint: \( \Sigma|w-w_{0}|\leq to_{h} \), where \( w_{0} \) is the previous period's weight [56][57][59] **Model Evaluation**: The model effectively balances factor exposure and practical constraints, ensuring stable returns and avoiding excessive concentration in specific stocks [60] --- Quantitative Factors and Construction Methods - **Factor Name**: Six-Month UMR **Factor Construction Idea**: The six-month UMR factor measures risk-adjusted momentum over a six-month window, capturing medium-term momentum trends [19][8][44] **Factor Construction Process**: - The UMR (Up-Minus-Down Ratio) is calculated as the ratio of upward movements to downward movements in stock prices over a specified period - The six-month UMR specifically uses a six-month window to compute this ratio, adjusted for risk [19][8][44] **Factor Evaluation**: This factor demonstrates strong performance in various index spaces, particularly in the CSI 500 and CSI All Share indices, indicating its effectiveness in capturing medium-term momentum [8][44] - **Factor Name**: Three-Month UMR **Factor Construction Idea**: Similar to the six-month UMR, this factor focuses on shorter-term momentum trends over a three-month window [19][8][44] **Factor Construction Process**: - The three-month UMR is calculated using the same methodology as the six-month UMR but with a three-month window for data aggregation [19][8][44] **Factor Evaluation**: This factor shows consistent performance across multiple indices, including the CSI 500 and CSI All Share indices, making it a reliable short-term momentum indicator [8][44] - **Factor Name**: Pre-Tax Earnings to Total Market Value (EPTTM) **Factor Construction Idea**: This valuation factor evaluates the earnings yield of a stock, providing insights into its relative valuation [19][8][44] **Factor Construction Process**: - EPTTM is calculated as the ratio of pre-tax earnings to the total market value of a stock, with adjustments for rolling time windows (e.g., one year) [19][8][44] **Factor Evaluation**: EPTTM consistently ranks among the top-performing valuation factors, particularly in the CSI 300 and CSI 800 indices, reflecting its robustness in identifying undervalued stocks [8][44] --- Backtesting Results of Models - **MFE Portfolio**: - The MFE portfolio demonstrates strong performance under various constraints, with backtesting results showing significant alpha generation relative to benchmarks like CSI 300, CSI 500, and CSI 1000 [60][61] --- Backtesting Results of Factors - **Six-Month UMR**: - CSI 500: Weekly return of 0.99%, monthly return of 1.65%, annualized return of -4.07% [26] - CSI All Share: Weekly return of 1.23%, monthly return of 1.59%, annualized return of 7.43% [44] - **Three-Month UMR**: - CSI 500: Weekly return of 0.94%, monthly return of 1.31%, annualized return of 0.68% [26] - CSI All Share: Weekly return of 1.02%, monthly return of 1.63%, annualized return of 5.64% [44] - **EPTTM**: - CSI 300: Weekly return of 0.74%, monthly return of 1.42%, annualized return of 3.89% [22] - CSI 800: Weekly return of 1.00%, monthly return of 1.91%, annualized return of 2.87% [30]